A selected reaction monitoring mass spectrometric assessment of biomarker candidates diagnosing large-cell neuroendocrine lung carcinoma by the scaling method using endogenous references

Proteomic Profiling of Small-Cell Lung Cancer: A Systematic Review

The accurate diagnosis of small-cell lung cancer (SCLC) is crucial, as treatment strategies differ from those of other lung cancers. This systematic review aims to identify proteins differentially expressed in SCLC compared to normal lung tissue, evaluating their potential utility in diagnosing and prognosing the disease. Additionally, the study identifies proteins differentially expressed between SCLC and large cell neuroendocrine carcinoma (LCNEC), aiming to discover biomarkers distinguishing between these two subtypes of neuroendocrine lung cancers. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search was conducted across PubMed/MEDLINE, Scopus, Embase, and Web of Science databases. Studies reporting proteomics information and confirming SCLC and/or LCNEC through histopathological and/or cytopathological examination were included, while review articles, non-original articles, and studies based on animal samples or cell lines were excluded. The initial search yielded 1705 articles, and after deduplication and screening, 16 articles were deemed eligible. These studies revealed 117 unique proteins significantly differentially expressed in SCLC compared to normal lung tissue, along with 37 unique proteins differentially expressed between SCLC and LCNEC. In conclusion, this review highlights the potential of proteomics technology in identifying novel biomarkers for diagnosing SCLC, predicting its prognosis, and distinguishing it from LCNEC.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Neoplastic signatures: Comparative proteomics of canine hepatobiliary neuroendocrine tumors to normal niche tissue

Hepatobiliary neuroendocrine neoplasms are rare cancers in humans and dogs. To date, no large-scale primary hepatobiliary neoplasm omics analyses exist in any species. This limits the development of diagnostic biomarkers and targeted therapeutics. Neuroendocrine cancers are a heterogenous group of neoplasms categorized by their tissue-of-origin. Because the anatomic niche of neuroendocrine neoplasms shapes tumor phenotype, we sought to compare the proteomes of 3 canine hepatobiliary neoplasms to normal hepatobiliary tissue and adrenal glands with the objective of identifying unique protein signatures. Protein was extracted from formalin-fixed paraffin-embedded samples and submitted for tandem mass spectroscopy. Thirty-two upregulated and 126 downregulated differentially expressed proteins were identified. Remarkably, 6 (19%) of the upregulated proteins are correlated to non-hepatobiliary neuroendocrine neoplasia and 16 (50%) are functionally annotated within the exosome cellular compartment key to neuroendocrine signaling. Twenty-six (21%) downregulated proteins are enriched in metabolic pathways consistent with alterations in cancer. These results suggests that characteristic neoplastic protein signatures can be gleaned from small data sets using a comparative proteomics approach.

Proteomic Signature of Extracellular Vesicles for Lung Cancer Recognition

The proteins of extracellular vesicles (EVs) that originate from tumors reflect the producer cells' proteomes and can be detected in biological fluids. Thus, EVs provide proteomic signatures that are of great interest for screening and predictive cancer diagnostics. By applying targeted mass spectrometry with stable isotope-labeled peptide standards, we assessed the levels of 28 EV-associated proteins, including the conventional exosome markers CD9, CD63, CD81, CD82, and HSPA8, in vesicles derived from the lung cancer cell lines NCI-H23 and A549. Furthermore, we evaluated the detectability of these proteins and their abundance in plasma samples from 34 lung cancer patients and 23 healthy volunteers. The abundance of TLN1, TUBA4A, HSPA8, ITGB3, TSG101, and PACSIN2 in the plasma of lung cancer patients was measured using targeted mass spectrometry and compared to that in plasma from healthy volunteers. The most diagnostically potent markers were TLN1 (AUC, 0.95), TUBA4A (AUC, 0.91), and HSPA8 (AUC, 0.88). The obtained EV proteomic signature allowed us to distinguish between the lung adenocarcinoma and squamous cell carcinoma histological types. The proteomic cargo of the extracellular vesicles represents a promising source of potential biomarkers.

Nucleocytoplasmic Proteomic Analysis Uncovers eRF1 and Nonsense-Mediated Decay as Modifiers of ALS/FTD C9orf72 Toxicity

The most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is a hexanucleotide repeat expansion in C9orf72 (C9-HRE). While RNA and dipeptide repeats produced by C9-HRE disrupt nucleocytoplasmic transport, the proteins that become redistributed remain unknown. Here, we utilized subcellular fractionation coupled with tandem mass spectrometry and identified 126 proteins, enriched for protein translation and RNA metabolism pathways, which collectively drive a shift toward a more cytosolic proteome in C9-HRE cells. Among these was eRF1, which regulates translation termination and nonsense-mediated decay (NMD). eRF1 accumulates within elaborate nuclear envelope invaginations in patient induced pluripotent stem cell (iPSC) neurons and postmortem tissue and mediates a protective shift from protein translation to NMD-dependent mRNA degradation. Overexpression of eRF1 and the NMD driver UPF1 ameliorate C9-HRE toxicity in vivo. Our findings provide a resource for proteome-wide nucleocytoplasmic alterations across neurodegeneration-associated repeat expansion mutations and highlight eRF1 and NMD as therapeutic targets in C9orf72-associated ALS and/or FTD.

Early urine proteome changes in the Walker-256 tail-vein injection rat model

Detection of cancer at its early stage is important for treatment. Urine, which is not regulated by homeostatic mechanisms, reflects early systemic changes throughout the whole body and can be used for the early detection of cancer. In this study, the Walker-256 tail-vein injection rat model was established to find whether the urine proteome could reflect early changes if tumor grown in lung. Urine samples from the control group (n = 7) and Walker-256 tail-vein injection group (n = 7) on days 2, 4, 6 and 9 were analyzed by label-free proteomic quantitative methods. On day 2, when lung tumor nodules did not appear, 62 differential proteins were identified. They were associated with epithelial cell differentiation, regulation of immune system processes and the classical complement activation pathway. On day 4, when lung tumor nodules appeared, 72 differential proteins were identified. They were associated with the innate immune response and positive regulation of phagocytosis. On day 6, when body weight began to decrease, 117 differential proteins were identified. On day 9, the identified 125 differential proteins were associated with the B cell receptor signaling pathway and the positive regulation of B cell activation. Our results indicate that (1) the urine proteome changed even on the second day after tail-vein injection of Walker-256 cells and that (2) compared to previous studies, the urine proteomes were different when the same cancer cells were grown in different organs.

Development of drug discovery screening system by molecular interaction kinetics-mass spectrometry

RATIONALE

Drug discovery studies invariably require qualitative and quantitative analyses of target compounds at every stage of drug discovery. We have developed a system combining molecular interaction analysis and mass spectrometry (LC-MS) using the principle of nanopore optical interferometry (nPOI) called molecular interaction kinetics-mass spectrometry (MIK-MS). Since nPOI has high binding capacity, the bond-dissociated compound can be directly detected using LC-MS. In this study, we use carbonic anhydrase II (CAII) as a ligand and apply six small compounds as analytes and report the affinity analysis using MIK-MS.

METHODS

CAII was immobilized onto a COOH sensor chip using standard amine coupling. A reference surface was prepared by activating and subsequently blocking the surface under identical conditions. An amount of 50 μL of mix solution was injected over the reference channel and sample channel for CAII immobilization. The solutions eluting from the sensor chip were collected from the waste-line of the SKi Pro system every 30 s. Reconstructed elution samples were then injected into the LC-MS/MS system.

RESULTS

A mixture containing furosemide, acetazolamide, 4-sulfamoylbenzoic acid, 5-(dimethylamino)-1-naphthalene sulfonamide (DNSA), sulfanilamide and sulpiride (15 μM each) was injected into the CAII-immobilized sensor chip, and the fractions eluted from the SKi Pro system were collected and subjected to selected reaction monitoring LC-MS characterization. Specific results were obtained for acetazolamide, DNSA, furosemide and sulpiride. The results suggest that the association-dissociation curve of a mixed sample can be obtained by one-time MIK-MS analysis.

CONCLUSIONS

Six small-molecule binders of CAII were analyzed quantitatively using nPOI and MIK-MS, and the results were compared to published surface plasmon resonance (SPR) results. The nPOI and SPR results show good agreement, confirming the reliability of the analysis. Time-dependent binding results may be obtained by our MS sensorgram approach. Drugs that meet medical needs in a short period are required; this nPOI-LC-MS system is considered an important tool for rapid drug discovery.